LEADER 01296nam0 2200277 450 001 000028503 005 20110516150054.0 100 $a20110516d2011----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $a----m-------- 200 1 $aStudio numerico e validazione del Vortex Method per applicazioni di tipo ingegneristico$bTesi di dottorato$fdottorando: Patrizia D'Andria$gcoordinatore del dottorato: Vinicio Magi$grelatore: Vinicio Magi 210 $a[Potenza]$d[2011] 215 $a68 p.$d30 cm. 328 1$aSul frontespizio: Università della Basilicata, Dottorato di ricerca in Ingegneria industriale e dell'innovazione, XXIII ciclo, A. a. 2009-2010 676 $a532.0595$v(21. ed.)$9Meccanica dei fluidi. Meccanica dei liquidi. Moto vorticoso 686 $aING-IND/08$9Macchine a fluido 700 1$aD'Andria,$bPatrizia$0445223 801 0$aIT$bUniversità della Basilicata - B.I.A.$gRICA$2unimarc 912 $a000028503 996 $aStudio numerico e validazione del Vortex Method per applicazioni di tipo ingegneristico$995435 997 $aUNIBAS BAS $aINGEGNERIA CAT $aTTM$b30$c20110516$lBAS01$h1500 FMT Z30 -1$lBAS01$LBAS01$mBOOK$1BASA2$APolo Tecnico-Scientifico$2TDO$BTesi di Dottorato$3TDI.23c.DP1$528506-10$820110516$f98$FConsultazione LEADER 01266nam--2200385---450- 001 990005825260203316 005 20130405113449.0 010 $a978-8858201701 035 $a000582526 035 $aUSA01000582526 035 $a(ALEPH)000582526USA01 035 $a000582526 100 $a20130405d2012----km-y0itay50------ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $a<> nuova responsabilità del medico dopo la legge Balduzzi$eaggiornato L. 8 novembre 2012, n. 189, recante disposizioni urgenti per la tutela della salute$fMarco De Luca 210 $aRoma$cDIKEgiuridica$d2012 215 $aVII, 314 p.$d24 cm 225 2 $a<> nuove leggi del diritto 410 0$12001$a<> nuove leggi del diritto 454 1$12001 461 1$1001-------$12001 607 0 $aMedici$xResponsabilità$2BNCF 676 $a344.4504121 700 1$aDE LUCA,$bMarco$0461877 801 0$aIT$bsalbc$gISBD 912 $a990005825260203316 951 $aXXV.1.K. 314$b76217 G.$cXXV.1.K.$d00291744 959 $aBK 969 $aGIU 979 $aFIORELLA$b90$c20130405$lUSA01$h1130 979 $aFIORELLA$b90$c20130405$lUSA01$h1134 996 $aNuova responsabilità del medico dopo la legge Balduzzi$9254256 997 $aUNISA LEADER 04095oam 2200541 450 001 9910437895203321 005 20190911103512.0 010 $a1-4614-6489-7 024 7 $a10.1007/978-1-4614-6489-1 035 $a(OCoLC)829681844 035 $a(MiFhGG)GVRL6YNU 035 $a(EXLCZ)993360000000455739 100 $a20121231d2013 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aPhonetic search methods for large speech databases /$fAmi Moyal [and three others] 205 $a1st ed. 2013. 210 1$aNew York :$cSpringer,$d2013. 215 $a1 online resource (x, 53 pages) $cillustrations (some color) 225 1 $aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,$x2191-737X 300 $a"ISSN: 2191-8112." 311 $a1-4614-6488-9 320 $aIncludes bibliographical references (pages 49-53). 327 $aKeyword Spotting out of Continuous Speech -- Introduction -- Problem Formulation: KWS in Large Speech Databases -- Target Applications of Keyword Spotting -- Keyword Spotting Methods -- LVCSR-Based KWS -- Acoustic KWS -- Phonetic Search KWS -- Discussion: Why Phonetic Search? -- Response Time -- KWS Performance -- Keyword Flexibility -- Phonetic Search -- The Search Mechanism -- Using Phonetic Search for KWS -- Computational Complexity Analysis -- Search Space Complexity Reduction -- Overview -- Complexity Reduction in Phonetic Search -- Anchor-based Phonetic Search -- Evaluating Phonetic Search KWS -- Performance Metrics -- Evaluation Process -- Evaluation Databases -- Evaluation Results -- Exhaustive Search. - Textual Benchmark -- KWS on Speech -- Anchor-based Search -- Textual Benchmark -- Reduced Complexity KWS on Speech -- Multiple Thresholds -- Lessons Learned from the Evaluation -- Summary -- Glossary of Acronyms -- References. 330 $a?Phonetic Search Methods for Large Databases? focuses on Keyword Spotting (KWS) within large speech databases. The brief will begin by outlining the challenges associated with Keyword Spotting within large speech databases using dynamic keyword vocabularies. It will then continue by highlighting the various market segments in need of KWS solutions, as well as, the specific requirements of each market segment. The work also includes a detailed description of the complexity of the task and the different methods that are used, including the advantages and disadvantages of each method and an in-depth comparison. The main focus will be on the Phonetic Search method and its efficient implementation. This will include a literature review of the various methods used for the efficient implementation of Phonetic Search Keyword Spotting, with an emphasis on the authors? own research which entails a comparative analysis of the Phonetic Search method which includes algorithmic details. This brief is useful for researchers and developers in academia and industry from the fields of speech processing and speech recognition, specifically Keyword Spotting. 410 0$aSpringerBriefs in electrical and computer engineering.$pSpeech technology. 606 $aDatabase searching 606 $aKeyword searching 606 $aNatural language processing (Computer science) 606 $aSpeech processing systems 615 0$aDatabase searching. 615 0$aKeyword searching. 615 0$aNatural language processing (Computer science) 615 0$aSpeech processing systems. 676 $a025.04 700 $aMoyal$b Ami$4aut$4http://id.loc.gov/vocabulary/relators/aut$01058999 702 $aAharonson$b Vered$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aTetariy$b Ella$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aGishri$b Michal$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910437895203321 996 $aPhonetic Search Methods for Large Speech Databases$92503583 997 $aUNINA